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Ionospheric scintillation frequently occurs in equatorial, auroral and polar regions, posing a threat to the performance of the global navigation satellite system (GNSS). Thus, the detection of ionospheric scintillation is of great significance in regard to improving GNSS performance, especially when severe ionospheric scintillation occurs. Normal algorithms exhibit insensitivity in strong scintillation detection in that the natural phenomenon of strong scintillation appears only occasionally, and such samples account for a small proportion of the data in datasets relative to those for weak/moderate scintillation events. Aiming at improving the detection accuracy, we proposed a strategy combining an improved eXtreme Gradient Boosting (XGBoost) algorithm by using the synthetic minority, oversampling technique and edited nearest neighbor (SMOTE-ENN) resampling technique for detecting events imbalanced with respect to weak, medium and strong ionospheric scintillation. It outperformed the decision tree and random forest by 12% when using imbalanced training and validation data, for tree depths ranging from 1 to 30. For different degrees of imbalance in the training datasets, the testing accuracy of the improved XGBoost was about 4% to 5% higher than that of the decision tree and random forest. Meanwhile, the testing results for the improved method showed significant increases in evaluation indicators, while the recall value for strong scintillation events was relatively stable, above 90%, and the corresponding F1 scores were over 92%. When testing on datasets with different degrees of imbalance, there was a distinct increase of about 10% to 20% in the recall value and 6% to 11% in the F1 score for strong scintillation events, with the testing accuracy ranging from 90.42% to 96.04%.

During the strong ionospheric scintillation, global positioning system (GPS) signal will be frequently subjected to amplitude fading, phase errors, increased carrier Doppler frequency shift, and even loss of lock. Based on GPS L1 C/A signals during the last peak of the solar cycle at the low latitude site of Sao Jose dos Campos, Brazil (23.2S, 45.9W) from 2013 to 2015, the relationship between amplitude/phase scintillation and carrier frequency is analyzed, and probability distribution function (PDF) model is proposed to achieve corresponding relationship quantified. According to certain threshold of peak probability boundary, the proportional trends of carrier frequency widths on four levels of scintillation are presented. Detailed analysis implies that different levels of scintillation will influence the fluctuation of carrier frequency, which will provide useful guidance to set the receiver’s bandwidth with respect to the different scintillation levels and design the advanced tracking algorithm.

Ionospheric scintillation, characterized by deep fluctuation of signal intensity on amplitude and phase, poses threats to the global navigation satellite system (GNSS) tracking performance, even causing degradation in position and navigation in accuracy, integrity and continuity. To achieve higher performance of ionospheric scintillation detection, a method of machine learning is implied to attain automatic detection. Three levels of scintillation intensities and two types of scintillation features are investigated and compared. Based on data from Sao Jose dos Campos, Brazil (23.2S, 45.9W), training validation and prediction results show 99% accuracy approximately and above 96%, respectively. The analysis will provide useful guidance on ionospheric scintillation detection to make of great signification on design of advanced GNSS receiver and research of atmospheric layer and space weather.

A well-designed tracking loop is the core of a Global Navigation Satellite System (GNSS) receiver and plays a decisive role in estimating parameters and positioning. To solve the problem that classical scalar tracking may fail to track the received signal frequently in high-dynamic and weak signal environments, novel tracking loops based on optimal estimation are proposed by many researchers. Among them, Kalman-based and vector tracking are expected to have a better performance in improving the precision of measurements and positions. Considering their superiority and promising applications in deeply coupled GNSS/ inertial navigation system, the theoretical analysis and practical implementation are worthy of being further explored. In this paper, an EKF-based tracking loop which uses the outputs of coherent channels directly is proposed. And then, the implementation of a vector tracking frequency-locked and delay-locked loop is further proposed in detail. At last, the performance and superiority of the two methods are tested where a software-defined receiver is constructed and the aircraft data from a GNSS constellation simulator is used. Compared with scalar tracking, a significant improvement on positioning and measuring parameters is achieved by the two methods. And the vector tracking indicates a 42.9% and a increase on the precision of positioning and pseudo-range measuring respectively.

L2C is the second civilian signal broadcasted on the modernized block of GPS satellites. Compared with L1C/A, the length of L2C code is longer, and includes the civil moderate code (CM code, 20ms) and the civil long code (CL code, 1.5s), which are based on time division multiplexing. For the long CL code, rapid acquisition is difficult due to the large search space. To accelerate the search process and improve detection performance, a fast direct GPS L2C CL signal acquisition algorithm based on time-frequency dual folding technique is introduced in this paper. By folding both the incoming and local signals, the method can be used to significantly accelerate the acquisition speed, and the degraded code correlation properties are insignificant. The effectiveness of the method of fast direct acquisition algorithm based on the time-frequency folding technique is proven through both theoretical performance analysis and real GPS L2C signal experiments.

To accurately evaluate the applicability of optimal coning algorithms, the direct influence of their periodic components on attitude accuracy is investigated. The true value of the change of the rotation vector is derived from the classical coning motion for analytic comparison. The analytic results show that the influence of periodic components is mostly dominant in two types of optimal coning algorithms. Considering that the errors of periodic components cannot be simply neglected, these algorithms are categorized with simplified forms. A variety of simulations are done under the classical coning motion. The numerical results are in good agreement with the analytic deductions. Considering their attitude accuracy, optimal coning algorithms of the 4-subinterval and 5-subinterval algorithms optimized with angular increments are not recommended for use for real application. Defence Science Journal, 2012, 62(6), pp.361-368 , DOI:http://dx.doi.org/10.14429/dsj.62.1430

In this paper, MBOC (Multiplexed Binary Offset Carrier) Signal which is recommended as the optimized modulation on L1 (E1) frequency band by both US and EU sides in the future was studied. This paper carried on the detailed analysis to the new MBOC signal characteristic through the analysis of the power spectral density function. Then two multipath mitigation techniques based on DLL (Delay Lock Loop) — strobe correlator and narrow correlator with basic functionality and implementation were introduced. These two techniques were applied to mitigate the multipath's influence on MBOC signals. Simulation based on Matlab tool was analyzed and the performance was compared with the BOC signals.

In a global positioning system receiver, the tracking algorithm plays a dominant role since the code delay and Doppler frequency shift need to be accurately estimated as well as their variation over time need to be continuously updated. Combine unscented Kalman filter (UKF) with CM/CL signal to improve the signal tracking precision is proposed. It allow weighting assignment between CM code and CL code incoming signal, masked by a mass of noise, and to describe a UKF tracking loop aiming at decreasing numerical errors. UKF here involves state and measuring equations which calculate absolute offsets to adjust initial code and carrier phase then dramatically decrease the tracking error. In particular, the algorithm is implemented in both open space and jammed environment to highlight the advantages of tracking approach, by comparing single code and combined code, UKF and EKF tracking loop. It proves that signal tracking based on UKF, with low energy dissipation as well as high precision, is particularly appealing for a software receiver implementation.